Advancing Edge Classification through High-Dimensional Causal Modeling of Node-Edge Interplay

ArXi:2605.00374v1 Announce Type: new Edge classification, a crucial task for graph applications, remains relatively under-explored compared to link prediction. Current methods often overlook the potential causal influences of node features on edge features, leading to a loss of relevant prior information. In this work, we present an empirical exploration using the Causal Edge Classification Framework